Change compute updates from periodic to on demand¶
Include the URL of your launchpad blueprint:
Currently, all compute nodes update status info in the DB on a periodic basis (the period is currently 60 seconds). Given that the status of the node only changes at specific points (mainly image creation/destruction) this leads to significant DB overhead on a large system. This BP changes the update mechanism to only update the DB when a node state changes, specifically at node startup, instance creation and instance destruction.
The status information about compute nodes is updated into the DB on a periodic basis. This means that every compute node in the system updates a row in the DB once every 60 seconds (the default period for this update). This is unnecessary and a scalability problem given that the status info is mostly static and doesn’t change very often, mainly it changes when an instance is created or destroyed.
Compute node only sends an update if its status changes. On a periodic interval (using the current default period of 60 seconds) the compute node will compare its status with the status saved from the last update. Only if the state or claims have changed will the DB be updated.
The advantage to this method is that it should significantly cut down on the number of DB updates while changing almost nothing about the way the system currently works, compute node changes will still take 60 seconds before they are updated but any change, for any reason, will ultimately be reported.
One potential issue with this is a possible sensitivity concern, updates shouldn’t be constantly sent if, for example, steady state system activity causes something like RAM usage to change slightly. Some experiments will have to be run to decide if adding in a sensitivity control for certain status metrics is needed. This can be a follow on optimization, if it’s necessary, since this design is no worse than the current mechanism.
Another idea would be to only update the DB at certain well defined events. The update code would only be called at system start up, instance creation and instance deletion. This would reduce the latency for status updates (the DB is modified as soon as the system state changes) but it suffers from some disadvantages:
1) Finding all of the appropriate events to record a status change. Are statup/creation/destruction the only places where the system state changes, maybe there are other events that should be tracked.
2) Future changes could add new events that change status and recognizing that an update is needed is an easy mistake to miss.
3) Status could change unknown to the nova code, imagine something like a hot plug add of memory.
Data model impact¶
There is no change to the data that is being stored in the DB, all of the current fields are stored exactly as before, this BP is just changing the frequency at which those fields are updated.
REST API impact¶
Other end user impact¶
As measured by DB updates this change will clearly cause no more DB updates than the current technique and, assuming instances are created on a node at a rate of less then one every 60 seconds, should cause much fewer DB updates.
Other deployer impact¶
- Primary assignee:
Don Dugger <email@example.com>
Change should be fairly simple, change the current update code to only update the DB if a ‘state_modified’ routine returns true. The ‘state_modified’ routine returns false if the current state matches the last recorded state. Otherwise, it saves the current state as the last recorded state and returns true.
The ‘state_modified’ routine maintains an in memory copy of the current status of the compute node. This copy of the state is compared with the current state and the update to the DB only happens if the copy and the current state differ. Note that the in memory copy is initialized to zero values on node startup so that the first periodic update call will find a miss match between the two states and the DB will be updated.
Based upon experiments it has been determined that a simple comparison of the entire current vs. the saved state is sufficient. If, in the future, more rapidly changing data that shouldn’t be stored in the DB is added to the compute node state then ‘state_modified’ can be easily changed to ignore such data that isn’t needed in the DB.
A unit test will be created to make sure that the DB is updated when the compute node status changes and is not updated when the status doesn’t change.
Section 5 of the Associate Training Guide
is slightly incorrect and should be fixed. It currently says “All compute nodes (also known as hosts in terms of OpenStack) periodically publish their status, resources available and hardware capabilities to nova-scheduler through the queue.” This should be modified to reflect that the status is updated in the DB which is then queried by the scheduler. (Note this is a generic fix that is really unrelated to this blueprint.)